https://github.com/trailofbits/maat

Open-source symbolic execution framework: https://maat.re
https://github.com/trailofbits/maat

Last synced: 3 months ago
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Open-source symbolic execution framework: https://maat.re

• Host: GitHub
• URL: https://github.com/trailofbits/maat
• Owner: trailofbits
• License: other
• Created: 2021-10-19T09:23:10.000Z (about 3 years ago)
• Default Branch: master
• Last Pushed: 2024-02-15T21:01:36.000Z (9 months ago)
• Last Synced: 2024-07-21T09:22:13.888Z (4 months ago)
• Language: C++
• Size: 7.26 MB
• Stars: 607
• Watchers: 15
• Forks: 44
• Open Issues: 28
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md

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• awesome-hacking-lists - trailofbits/maat - Open-source symbolic execution framework: https://maat.re (C++)

README

        


     



 


  

  


  


  




# About

Maat is an open-source Dynamic Symbolic Execution and Binary Analysis framework. It provides various functionalities such as symbolic execution, taint analysis, constraint solving, binary loading, environment simulation, and leverages Ghidra's sleigh library for assembly lifting: https://maat.re

Key features:

- **Fast & Portable**: Designed to scale to real-world applications. Fully written in C++ for good runtime

                performance. There are hardly any runtime dependencies, and most of them are optional

- **User-friendly**: Maat has a flexible debugger-like API, and its features are configurable to

                      adapt to many different use-cases. As any self-respecting modern framework, it comes with *Python bindings*

- **Multi-arch**: With lifting and emulation based on Ghidra's awesome *sleigh* library, Maat

                      has the potential to emulate many architectures, including exotic ones

# Getting started

- [Installation](#installation)

- [Hacking](./HACKING.md)

- [Contributing](./CONTRIBUTING.md)

- [Tutorials](https://maat.re/tutorials.html)

     - [Getting started](https://maat.re/tutorials/get_started.html)

     - [Event hooking](https://maat.re/tutorials/events.html)

     - [Dynamic symbolic execution](https://maat.re/tutorials/dse.html)

- [Documentation](https://maat.re/python_api/index.html)

     - [Python API](https://maat.re/python_api/index.html)

     - [C++ API](https://maat.re/cpp_api/index.html)

- [Example](#example)

- [Contact](#contact)

# Installation

To install Maat's python module:

````

python3 -m pip install pymaat

````

To install Maat's native SDK and use the C++ API, check out [BUILDING.md](./BUILDING.md)

# Example

```Python

from maat import *

# Create a symbolic engine for Linux X86-32bits

engine = MaatEngine(ARCH.X86, OS.LINUX)

# Load a binary with one command line argument

engine.load("./some_binary", BIN.ELF32, args=[engine.vars.new_symbolic_buffer("some_arg", 20)])

# Get current eax value

engine.cpu.eax

# Read 4 bytes at the top of the stack

engine.mem.read(engine.cpu.esp, 4)

# Set a callback displaying every memory read

def show_mem_access(engine):

    mem_access = engine.info.mem_access

    print(f"Instruction at {engine.info.addr} reads {mem_access.size} bytes at {mem_access.addr}")

engine.hooks.add(EVENT.MEM_R, WHEN.BEFORE, callbacks=[show_mem_access])

# Take and restore snapshots

snap = engine.take_snapshot()

engine.restore_snapshot(snap)

# Run the binary

engine.run()

```

# Contact

For general discussions, questions and suggestions, we use [Github Discussions](https://github.com/trailofbits/maat/discussions)

For reporting issues and bugs, please use [Github Issues](https://github.com/trailofbits/maat/issues)

For anything else, drop an e-mail at [email protected]